SAR Water Image Segmentation Based on GLCM and Wavelet Textures

Combination of gray water and land SAR image and wavelet texture information, present a new segmentation method of SAR image surface. Firstly, extracting gray level co-occurrence matrix of the sub-blocks SAR image, then using wavelet transform to extract the norm and the average deviation as the wavelet texture feature information of sub-blocks of sub-image; Accordingly, two types of texture establish a suitable combination of image separation measure multi-dimensional feature space; Finally, using K-means clustering algorithm to segment the SAR water image. The experimental results show that the effect is better than the common segmentation method.